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add usability to problem section in epi-community-contrib post
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posts/epi-community-contrib/index.qmd

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Software that is developed for research or by researchers can be difficult to maintain given the incentive and funding structures in academia. This remains true for epidemiology, with a large volume of software written during the COVID-19 pandemic, much of which is now abandonware[^1]. This does not mean that the software developed to understand the COVID-19 pandemic was bad or does not have utility in understanding future epidemics and pandemics, but just that the capacity to maintain and further develop these tools is not available now the pandemic is no [longer considered an acute public health emergency](https://www.who.int/news/item/05-05-2023-statement-on-the-fifteenth-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-coronavirus-disease-(covid-19)-pandemic).
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These issues around software sustainability and the academic structures that hinder software longevity were raised by @kucharskiCOVID19ResponseIllustrates2020 and were one of the leading reasons for the [Epiverse-TRACE initiative](https://epiverse-trace.github.io/). Alongside the developing novel software (R packages), Epiverse also has a commitment to support the community of package developers in epidemiology and outbreak analytics. The initiative also tries to improve community collaboration and contribution friendliness of open-source software.
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These issues around software sustainability and the academic structures that hinder software longevity were raised by @kucharskiCOVID19ResponseIllustrates2020 and were one of the leading reasons for the [Epiverse-TRACE initiative](https://epiverse-trace.github.io/). Alongside the developing novel software (R packages), Epiverse also has a commitment to support the community of package developers in epidemiology and outbreak analytics. The initiative also tries to improve community collaboration and contribution friendliness of open-source software.
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This blog post highlights some recent work by Epiverse software engineers to collaborate on research software, or researchware, to help develop an R package that was initially written in the early days of the COVID-19 pandemic (January 2020 - May 2020) to assess the effectiveness of isolation and contact tracing effectiveness [@hellewellFeasibilityControllingCOVID192020]. It built on code written for the 2014-2016 West Africa Ebola outbreak to provide insights into ring vaccination [@kucharskiEffectivenessRingVaccination2016]. These applications and the general nature of the questions the package addresses suggest that it could be of great help in future infectious disease outbreaks, but has been dormant for the past few years.
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## The problem
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It is understandable that because {ringbp} was written in haste to produce insights to inform pandemic response it did not adhere to all software best practices. Documentation, testing, code style and (computational) performance could be improved. Certain aspects of model code, like parameterisations, were hard-coded, not providing users the full flexibility that the model could allow.
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It is understandable that because {ringbp} was written in haste to produce insights to inform pandemic response it did not adhere to all software best practices. Usability, documentation, testing, code style and (computational) performance could be improved. Certain aspects of model code, like parameterisations, were hard-coded, not providing users the full flexibility that the model could allow.
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## Epiverse contribution
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